Overview

Dataset statistics

Number of variables14
Number of observations5694
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory667.3 KiB
Average record size in memory120.0 B

Variable types

Numeric14

Alerts

monetary is highly overall correlated with unique_prods and 5 other fieldsHigh correlation
unique_prods is highly overall correlated with monetary and 3 other fieldsHigh correlation
qt_prods is highly overall correlated with monetary and 4 other fieldsHigh correlation
avg_basket_size is highly overall correlated with unique_prods and 2 other fieldsHigh correlation
recency is highly overall correlated with relationship_duration and 2 other fieldsHigh correlation
relationship_duration is highly overall correlated with monetary and 5 other fieldsHigh correlation
purchase_count is highly overall correlated with monetary and 6 other fieldsHigh correlation
returns_count is highly overall correlated with relationship_duration and 2 other fieldsHigh correlation
return_rate is highly overall correlated with returns_countHigh correlation
avg_purchase_interval is highly overall correlated with monetary and 4 other fieldsHigh correlation
frequency is highly overall correlated with relationship_duration and 2 other fieldsHigh correlation
avg_order_value is highly overall correlated with monetary and 3 other fieldsHigh correlation
monetary is highly skewed (γ1 = 23.70954924)Skewed
returns_count is highly skewed (γ1 = 30.34234755)Skewed
avg_unit_price is highly skewed (γ1 = 40.01799359)Skewed
return_rate is highly skewed (γ1 = 46.64019057)Skewed
avg_purchase_interval is highly skewed (γ1 = 67.66998836)Skewed
avg_order_value is highly skewed (γ1 = 21.19544146)Skewed
customer_id has unique valuesUnique
relationship_duration has 2921 (51.3%) zerosZeros
returns_count has 4191 (73.6%) zerosZeros
return_rate has 4191 (73.6%) zerosZeros
avg_purchase_interval has 2921 (51.3%) zerosZeros

Reproduction

Analysis started2023-06-25 19:50:12.725593
Analysis finished2023-06-25 19:50:42.190463
Duration29.46 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Distinct5694
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16601.346
Minimum12347
Maximum22709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:42.305967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12700.65
Q114289.25
median16228
Q318210.75
95-th percentile21731.95
Maximum22709
Range10362
Interquartile range (IQR)3921.5

Descriptive statistics

Standard deviation2807.9223
Coefficient of variation (CV)0.16913823
Kurtosis-0.82113706
Mean16601.346
Median Absolute Deviation (MAD)1961.5
Skewness0.44131147
Sum94528065
Variance7884427.6
MonotonicityStrictly increasing
2023-06-25T16:50:42.511478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12347 1
 
< 0.1%
17596 1
 
< 0.1%
17562 1
 
< 0.1%
17561 1
 
< 0.1%
17560 1
 
< 0.1%
17557 1
 
< 0.1%
17556 1
 
< 0.1%
17555 1
 
< 0.1%
17554 1
 
< 0.1%
17553 1
 
< 0.1%
Other values (5684) 5684
99.8%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12349 1
< 0.1%
12350 1
< 0.1%
12352 1
< 0.1%
12353 1
< 0.1%
12354 1
< 0.1%
12355 1
< 0.1%
12356 1
< 0.1%
12357 1
< 0.1%
ValueCountFrequency (%)
22709 1
< 0.1%
22708 1
< 0.1%
22707 1
< 0.1%
22706 1
< 0.1%
22705 1
< 0.1%
22704 1
< 0.1%
22700 1
< 0.1%
22699 1
< 0.1%
22696 1
< 0.1%
22695 1
< 0.1%

monetary
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5450
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1721.4744
Minimum-796.86
Maximum278778.02
Zeros9
Zeros (%)0.2%
Negative3
Negative (%)0.1%
Memory size89.0 KiB
2023-06-25T16:50:42.682662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-796.86
5-th percentile12.486
Q1230.2875
median603.555
Q31547.795
95-th percentile5196.0935
Maximum278778.02
Range279574.88
Interquartile range (IQR)1317.5075

Descriptive statistics

Standard deviation7366.685
Coefficient of variation (CV)4.2792882
Kurtosis739.45922
Mean1721.4744
Median Absolute Deviation (MAD)475.405
Skewness23.709549
Sum9802075
Variance54268048
MonotonicityNot monotonic
2023-06-25T16:50:42.857567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
0.2%
7.95 9
 
0.2%
2.95 8
 
0.1%
1.25 8
 
0.1%
4.95 8
 
0.1%
3.75 7
 
0.1%
12.75 7
 
0.1%
1.65 7
 
0.1%
7.5 6
 
0.1%
4.25 6
 
0.1%
Other values (5440) 5619
98.7%
ValueCountFrequency (%)
-796.86 1
 
< 0.1%
-141.48 1
 
< 0.1%
-95.93 1
 
< 0.1%
0 9
0.2%
5.684341886 × 10-141
 
< 0.1%
4.547473509 × 10-131
 
< 0.1%
0.42 1
 
< 0.1%
0.65 1
 
< 0.1%
0.79 1
 
< 0.1%
0.84 4
0.1%
ValueCountFrequency (%)
278778.02 1
< 0.1%
259657.3 1
< 0.1%
189735.53 1
< 0.1%
133007.13 1
< 0.1%
123638.18 1
< 0.1%
114505.32 1
< 0.1%
88138.2 1
< 0.1%
65920.12 1
< 0.1%
62924.1 1
< 0.1%
59419.34 1
< 0.1%

unique_prods
Real number (ℝ)

Distinct439
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.681595
Minimum1
Maximum1786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:43.051485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q113
median36
Q384.75
95-th percentile241.35
Maximum1786
Range1785
Interquartile range (IQR)71.75

Descriptive statistics

Standard deviation101.73535
Coefficient of variation (CV)1.4600032
Kurtosis43.87754
Mean69.681595
Median Absolute Deviation (MAD)28
Skewness4.703277
Sum396767
Variance10350.081
MonotonicityNot monotonic
2023-06-25T16:50:43.253544image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 278
 
4.9%
2 149
 
2.6%
3 112
 
2.0%
10 101
 
1.8%
5 98
 
1.7%
9 96
 
1.7%
6 93
 
1.6%
8 93
 
1.6%
11 92
 
1.6%
4 90
 
1.6%
Other values (429) 4492
78.9%
ValueCountFrequency (%)
1 278
4.9%
2 149
2.6%
3 112
2.0%
4 90
 
1.6%
5 98
 
1.7%
6 93
 
1.6%
7 90
 
1.6%
8 93
 
1.6%
9 96
 
1.7%
10 101
 
1.8%
ValueCountFrequency (%)
1786 1
< 0.1%
1766 1
< 0.1%
1322 1
< 0.1%
1118 1
< 0.1%
1109 1
< 0.1%
884 1
< 0.1%
817 1
< 0.1%
748 1
< 0.1%
730 1
< 0.1%
720 1
< 0.1%

qt_prods
Real number (ℝ)

Distinct529
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.625571
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:43.465178image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114
median41
Q3106
95-th percentile332.35
Maximum7838
Range7837
Interquartile range (IQR)92

Descriptive statistics

Standard deviation210.59359
Coefficient of variation (CV)2.273601
Kurtosis510.23293
Mean92.625571
Median Absolute Deviation (MAD)33
Skewness17.752506
Sum527410
Variance44349.661
MonotonicityNot monotonic
2023-06-25T16:50:43.664131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 255
 
4.5%
2 149
 
2.6%
3 108
 
1.9%
10 101
 
1.8%
6 99
 
1.7%
9 92
 
1.6%
5 91
 
1.6%
4 87
 
1.5%
7 83
 
1.5%
11 83
 
1.5%
Other values (519) 4546
79.8%
ValueCountFrequency (%)
1 255
4.5%
2 149
2.6%
3 108
1.9%
4 87
 
1.5%
5 91
 
1.6%
6 99
 
1.7%
7 83
 
1.5%
8 81
 
1.4%
9 92
 
1.6%
10 101
 
1.8%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_basket_size
Real number (ℝ)

Distinct1255
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.991481
Minimum1
Maximum1113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:43.874032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3333333
Q19
median18
Q335.6125
95-th percentile175.35
Maximum1113
Range1112
Interquartile range (IQR)26.6125

Descriptive statistics

Standard deviation77.016374
Coefficient of variation (CV)1.9258195
Kurtosis32.294916
Mean39.991481
Median Absolute Deviation (MAD)11.267857
Skewness4.9956284
Sum227711.5
Variance5931.5219
MonotonicityNot monotonic
2023-06-25T16:50:44.384452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 282
 
5.0%
2 160
 
2.8%
3 116
 
2.0%
13 108
 
1.9%
10 103
 
1.8%
9 99
 
1.7%
6 95
 
1.7%
5 94
 
1.7%
4 92
 
1.6%
11 91
 
1.6%
Other values (1245) 4454
78.2%
ValueCountFrequency (%)
1 282
5.0%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1.5 7
 
0.1%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 160
2.8%
ValueCountFrequency (%)
1113 1
< 0.1%
748 1
< 0.1%
730 1
< 0.1%
720 1
< 0.1%
704 1
< 0.1%
686 1
< 0.1%
675 1
< 0.1%
674 1
< 0.1%
661 1
< 0.1%
650 1
< 0.1%

recency
Real number (ℝ)

Distinct304
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.89111
Minimum0
Maximum373
Zeros37
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:44.598449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q123
median71
Q3200
95-th percentile338
Maximum373
Range373
Interquartile range (IQR)177

Descriptive statistics

Standard deviation111.6221
Coefficient of variation (CV)0.95492377
Kurtosis-0.64121555
Mean116.89111
Median Absolute Deviation (MAD)61
Skewness0.81483305
Sum665578
Variance12459.494
MonotonicityNot monotonic
2023-06-25T16:50:44.762151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 110
 
1.9%
4 105
 
1.8%
3 98
 
1.7%
2 92
 
1.6%
10 86
 
1.5%
8 82
 
1.4%
9 79
 
1.4%
17 79
 
1.4%
7 78
 
1.4%
15 66
 
1.2%
Other values (294) 4819
84.6%
ValueCountFrequency (%)
0 37
 
0.6%
1 110
1.9%
2 92
1.6%
3 98
1.7%
4 105
1.8%
5 52
0.9%
7 78
1.4%
8 82
1.4%
9 79
1.4%
10 86
1.5%
ValueCountFrequency (%)
373 23
0.4%
372 23
0.4%
371 17
0.3%
369 4
 
0.1%
368 13
0.2%
367 16
0.3%
366 15
0.3%
365 19
0.3%
364 11
0.2%
362 7
 
0.1%

relationship_duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct374
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.368282
Minimum0
Maximum373
Zeros2921
Zeros (%)51.3%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:44.948334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3207
95-th percentile353
Maximum373
Range373
Interquartile range (IQR)207

Descriptive statistics

Standard deviation128.15686
Coefficient of variation (CV)1.289716
Kurtosis-0.80706617
Mean99.368282
Median Absolute Deviation (MAD)0
Skewness0.87305506
Sum565803
Variance16424.181
MonotonicityNot monotonic
2023-06-25T16:50:45.116547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2921
51.3%
364 28
 
0.5%
350 26
 
0.5%
357 25
 
0.4%
366 20
 
0.4%
351 20
 
0.4%
355 19
 
0.3%
365 18
 
0.3%
343 18
 
0.3%
356 17
 
0.3%
Other values (364) 2582
45.3%
ValueCountFrequency (%)
0 2921
51.3%
1 9
 
0.2%
2 4
 
0.1%
3 5
 
0.1%
4 4
 
0.1%
5 3
 
0.1%
6 2
 
< 0.1%
7 7
 
0.1%
8 5
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
373 5
 
0.1%
372 8
 
0.1%
371 8
 
0.1%
370 8
 
0.1%
369 6
 
0.1%
368 10
 
0.2%
367 11
 
0.2%
366 20
0.4%
365 18
0.3%
364 28
0.5%

purchase_count
Real number (ℝ)

Distinct56
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4717246
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:45.305740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile11
Maximum206
Range205
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.8138139
Coefficient of variation (CV)1.9626597
Kurtosis302.04793
Mean3.4717246
Median Absolute Deviation (MAD)0
Skewness13.1919
Sum19768
Variance46.42806
MonotonicityNot monotonic
2023-06-25T16:50:45.467116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2870
50.4%
2 825
 
14.5%
3 503
 
8.8%
4 394
 
6.9%
5 237
 
4.2%
6 173
 
3.0%
7 138
 
2.4%
8 98
 
1.7%
9 69
 
1.2%
10 55
 
1.0%
Other values (46) 332
 
5.8%
ValueCountFrequency (%)
1 2870
50.4%
2 825
 
14.5%
3 503
 
8.8%
4 394
 
6.9%
5 237
 
4.2%
6 173
 
3.0%
7 138
 
2.4%
8 98
 
1.7%
9 69
 
1.2%
10 55
 
1.0%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
< 0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
< 0.1%
60 1
< 0.1%
57 1
< 0.1%

returns_count
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct213
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.239902
Minimum0
Maximum9014
Zeros4191
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:45.630394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile38
Maximum9014
Range9014
Interquartile range (IQR)1

Descriptive statistics

Standard deviation204.94904
Coefficient of variation (CV)11.236302
Kurtosis1138.869
Mean18.239902
Median Absolute Deviation (MAD)0
Skewness30.342348
Sum103858
Variance42004.11
MonotonicityNot monotonic
2023-06-25T16:50:45.786781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
73.6%
1 169
 
3.0%
2 150
 
2.6%
3 105
 
1.8%
4 89
 
1.6%
6 78
 
1.4%
5 61
 
1.1%
12 52
 
0.9%
7 44
 
0.8%
8 43
 
0.8%
Other values (203) 712
 
12.5%
ValueCountFrequency (%)
0 4191
73.6%
1 169
 
3.0%
2 150
 
2.6%
3 105
 
1.8%
4 89
 
1.6%
5 61
 
1.1%
6 78
 
1.4%
7 44
 
0.8%
8 43
 
0.8%
9 41
 
0.7%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

avg_unit_price
Real number (ℝ)

Distinct5265
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7161781
Minimum0.06
Maximum434.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:45.984642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile1.2516557
Q12.2178856
median3.0488988
Q34.25
95-th percentile6.6996959
Maximum434.65
Range434.59
Interquartile range (IQR)2.0321144

Descriptive statistics

Standard deviation7.8496708
Coefficient of variation (CV)2.1122967
Kurtosis1952.5571
Mean3.7161781
Median Absolute Deviation (MAD)0.95889881
Skewness40.017994
Sum21159.918
Variance61.617331
MonotonicityNot monotonic
2023-06-25T16:50:46.144125image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.25 26
 
0.5%
4.95 20
 
0.4%
0.85 18
 
0.3%
3.75 16
 
0.3%
2.95 15
 
0.3%
1.65 14
 
0.2%
0.42 13
 
0.2%
2.08 13
 
0.2%
12.75 12
 
0.2%
2.55 12
 
0.2%
Other values (5255) 5535
97.2%
ValueCountFrequency (%)
0.06 1
< 0.1%
0.1225 1
< 0.1%
0.17 2
< 0.1%
0.2327777778 1
< 0.1%
0.29 2
< 0.1%
0.32 1
< 0.1%
0.33 1
< 0.1%
0.355 2
< 0.1%
0.358 1
< 0.1%
0.3666666667 1
< 0.1%
ValueCountFrequency (%)
434.65 1
< 0.1%
295 1
< 0.1%
125 1
< 0.1%
110 2
< 0.1%
74.975 1
< 0.1%
66.475 1
< 0.1%
59.73333333 1
< 0.1%
54.3 1
< 0.1%
51.71 1
< 0.1%
39.95 1
< 0.1%

return_rate
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct471
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5632628
Minimum0
Maximum3004.6667
Zeros4191
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:46.317068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.22222222
95-th percentile7.5
Maximum3004.6667
Range3004.6667
Interquartile range (IQR)0.22222222

Descriptive statistics

Standard deviation48.566706
Coefficient of variation (CV)13.629841
Kurtosis2669.7275
Mean3.5632628
Median Absolute Deviation (MAD)0
Skewness46.640191
Sum20289.219
Variance2358.7249
MonotonicityNot monotonic
2023-06-25T16:50:46.478548image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
73.6%
1 112
 
2.0%
2 81
 
1.4%
0.5 64
 
1.1%
3 52
 
0.9%
0.3333333333 43
 
0.8%
4 40
 
0.7%
1.5 33
 
0.6%
6 32
 
0.6%
0.25 29
 
0.5%
Other values (461) 1017
 
17.9%
ValueCountFrequency (%)
0 4191
73.6%
0.03571428571 1
 
< 0.1%
0.04761904762 1
 
< 0.1%
0.05 1
 
< 0.1%
0.05555555556 1
 
< 0.1%
0.07272727273 1
 
< 0.1%
0.07692307692 1
 
< 0.1%
0.08333333333 1
 
< 0.1%
0.09090909091 2
 
< 0.1%
0.1 6
 
0.1%
ValueCountFrequency (%)
3004.666667 1
< 0.1%
1228 1
< 0.1%
1006 1
< 0.1%
510 1
< 0.1%
426 1
< 0.1%
378.75 1
< 0.1%
336 1
< 0.1%
314 1
< 0.1%
312 1
< 0.1%
300 1
< 0.1%

avg_purchase_interval
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1229
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.030117058
Minimum0
Maximum34
Zeros2921
Zeros (%)51.3%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:46.649302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.023952096
95-th percentile0.076923077
Maximum34
Range34
Interquartile range (IQR)0.023952096

Descriptive statistics

Standard deviation0.46823463
Coefficient of variation (CV)15.547157
Kurtosis4874.1687
Mean0.030117058
Median Absolute Deviation (MAD)0
Skewness67.669988
Sum171.48653
Variance0.21924367
MonotonicityNot monotonic
2023-06-25T16:50:46.820299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2921
51.3%
0.07142857143 16
 
0.3%
0.04761904762 15
 
0.3%
0.02857142857 14
 
0.2%
0.0303030303 14
 
0.2%
0.01587301587 14
 
0.2%
0.06451612903 13
 
0.2%
0.02380952381 13
 
0.2%
0.1428571429 13
 
0.2%
0.025 12
 
0.2%
Other values (1219) 2649
46.5%
ValueCountFrequency (%)
0 2921
51.3%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005602240896 2
 
< 0.1%
0.005617977528 1
 
< 0.1%
0.005633802817 2
 
< 0.1%
0.005681818182 1
 
< 0.1%
0.005698005698 2
 
< 0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 6
0.1%
1.5 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1 4
0.1%
0.6666666667 3
0.1%
0.5522788204 1
 
< 0.1%
0.5349462366 1
 
< 0.1%

frequency
Real number (ℝ)

Distinct1226
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.54721716
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-25T16:50:47.002820image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.011042615
Q10.024924276
median1
Q31
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.97507572

Descriptive statistics

Standard deviation0.550273
Coefficient of variation (CV)1.0055843
Kurtosis139.14854
Mean0.54721716
Median Absolute Deviation (MAD)0
Skewness4.8594208
Sum3115.8545
Variance0.30280038
MonotonicityNot monotonic
2023-06-25T16:50:47.176595image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2878
50.5%
2 47
 
0.8%
0.0625 18
 
0.3%
0.02777777778 17
 
0.3%
0.02380952381 16
 
0.3%
0.08333333333 15
 
0.3%
0.09090909091 15
 
0.3%
0.03448275862 14
 
0.2%
0.02941176471 14
 
0.2%
0.02127659574 13
 
0.2%
Other values (1216) 2647
46.5%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
< 0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
< 0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
< 0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
4 1
 
< 0.1%
3 5
 
0.1%
2 47
 
0.8%
1.142857143 1
 
< 0.1%
1 2878
50.5%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%

avg_order_value
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5443
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean546.04678
Minimum-796.86
Maximum52940.94
Zeros9
Zeros (%)0.2%
Negative3
Negative (%)0.1%
Memory size89.0 KiB
2023-06-25T16:50:47.349402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-796.86
5-th percentile12.45
Q1156.3225
median289.295
Q3480.29792
95-th percentile1833.422
Maximum52940.94
Range53737.8
Interquartile range (IQR)323.97542

Descriptive statistics

Standard deviation1368.9567
Coefficient of variation (CV)2.5070319
Kurtosis715.70656
Mean546.04678
Median Absolute Deviation (MAD)149.33688
Skewness21.195441
Sum3109190.4
Variance1874042.4
MonotonicityNot monotonic
2023-06-25T16:50:47.519417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
0.2%
7.95 9
 
0.2%
1.25 8
 
0.1%
4.95 8
 
0.1%
2.95 8
 
0.1%
1.65 7
 
0.1%
7.5 7
 
0.1%
3.75 7
 
0.1%
12.75 7
 
0.1%
5.95 6
 
0.1%
Other values (5433) 5618
98.7%
ValueCountFrequency (%)
-796.86 1
 
< 0.1%
-141.48 1
 
< 0.1%
-47.965 1
 
< 0.1%
0 9
0.2%
5.684341886 × 10-141
 
< 0.1%
4.547473509 × 10-131
 
< 0.1%
0.42 1
 
< 0.1%
0.65 1
 
< 0.1%
0.79 1
 
< 0.1%
0.84 4
0.1%
ValueCountFrequency (%)
52940.94 1
< 0.1%
50653.91 1
< 0.1%
21389.6 1
< 0.1%
18745.86 1
< 0.1%
14855.53 1
< 0.1%
13206.5 1
< 0.1%
12681.58 1
< 0.1%
12633.67 1
< 0.1%
12172.09 1
< 0.1%
11540.34 1
< 0.1%

Interactions

2023-06-25T16:50:39.556423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.057322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.971249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.811220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.768946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.901568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.243098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.310521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.526685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.529254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.463611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.382628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:35.435385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.494621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:39.689591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.188374image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.099710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.944946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.906840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.056087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.380266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.468057image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.673309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.660448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.598951image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.517170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:35.571956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.635636image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:39.821645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.316586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.223168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.080010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:19.097243image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.193318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.533845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.619213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.813291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.798182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.726952image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.649500image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:35.726337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.778495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:39.982454image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.453230image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.356269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.218337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:19.260590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.359184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.693857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.785725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.953202image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.958461image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.863169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.789477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:35.873996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.932038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:40.124150image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.639194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.493766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.370973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:19.410358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.504188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.843231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.967000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.149057image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.107038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.003327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.952382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.036046image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.083989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:40.274011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.766712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.619621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.502919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:19.559283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.633151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.977070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:26.128302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.321268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.250422image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.135883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.103322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.178091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.220585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:40.417528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:13.905823image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.755523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.644321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:19.715949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.784990image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:24.123135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:26.286062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.456796image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.388417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.273876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.252839image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.325913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.372430image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:40.570456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.045973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:15.894476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.787369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:19.877246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:21.937321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:24.267088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:26.452824image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.601655image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.536413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.419881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.408579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.499965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.522229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:40.740497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.169971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.019761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:17.913503image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.012810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:22.145428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:24.396604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:26.595857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.737366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.663345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.548537image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.542339image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.640593image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.666034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:40.888424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.300191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.144093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.042343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.145425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:22.512881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:24.529512image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:26.744324image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.859376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.783864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.686637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.669875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.774784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.803999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:41.025354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.426599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.270703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.172591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.296365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:22.662432image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:24.666947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:26.892233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:28.986953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:30.911520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.809002image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.810679image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:36.913417image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:38.935432image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:41.182053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.559404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.405175image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.346418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.438325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:22.797375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:24.822344image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.043354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.116903image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.051973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:32.955489image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:34.968548image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.054744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:39.084223image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:41.343071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.695721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.546272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.494406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.599777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:22.960264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.002375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.206711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.256901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.188375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.109009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:35.128215image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.202672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:39.231554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:41.497424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:14.840216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:16.683634image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:18.636325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:20.763852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:23.111319image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:25.162551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:27.378383image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:29.394533image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:31.332941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:33.255022image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:35.292963image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:37.356320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T16:50:39.390112image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-06-25T16:50:47.673653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
customer_id1.000-0.174-0.017-0.0490.1130.245-0.382-0.383-0.2770.216-0.278-0.3810.380-0.032
monetary-0.1741.0000.7990.8390.494-0.4260.5960.6400.4060.0780.3710.544-0.4500.766
unique_prods-0.0170.7991.0000.9880.823-0.3270.4230.4500.2710.0630.2410.365-0.3120.642
qt_prods-0.0490.8390.9881.0000.768-0.3790.4970.5330.3170.0380.2820.438-0.3590.627
avg_basket_size0.1130.4940.8230.7681.000-0.038-0.038-0.047-0.0210.123-0.021-0.0640.0320.683
recency0.245-0.426-0.327-0.379-0.0381.000-0.598-0.597-0.3210.203-0.292-0.5190.486-0.086
relationship_duration-0.3820.5960.4230.497-0.038-0.5981.0000.9450.503-0.1620.4670.816-0.9100.071
purchase_count-0.3830.6400.4500.533-0.047-0.5970.9451.0000.539-0.1660.4970.902-0.7990.073
returns_count-0.2770.4060.2710.317-0.021-0.3210.5030.5391.000-0.0610.9940.465-0.3660.116
avg_unit_price0.2160.0780.0630.0380.1230.203-0.162-0.166-0.0611.000-0.058-0.1620.1530.202
return_rate-0.2780.3710.2410.282-0.021-0.2920.4670.4970.994-0.0581.0000.433-0.3540.113
avg_purchase_interval-0.3810.5440.3650.438-0.064-0.5190.8160.9020.465-0.1620.4331.000-0.7230.055
frequency0.380-0.450-0.312-0.3590.0320.486-0.910-0.799-0.3660.153-0.354-0.7231.000-0.043
avg_order_value-0.0320.7660.6420.6270.683-0.0860.0710.0730.1160.2020.1130.055-0.0431.000

Missing values

2023-06-25T16:50:41.716880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-06-25T16:50:42.053309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
012347.04310.0010318226.000000236570.02.6440110.00.0191780.019126615.714286
112348.01437.2421276.7500007528340.00.6929630.00.0141340.014085359.310000
212349.01457.55727272.00000018010.04.2375000.00.0000001.0000001457.550000
312350.0294.40161616.000000310010.01.5812500.00.0000001.000000294.400000
412352.01265.41577711.00000036260763.04.0754559.00.0269230.026820180.772857
512353.089.00444.000000204010.06.0750000.00.0000001.00000089.000000
612354.01079.40585858.000000232010.04.5037930.00.0000001.0000001079.400000
712355.0459.40131313.000000214010.04.2038460.00.0000001.000000459.400000
812356.02487.43525819.3333332230330.02.9460340.00.0099010.009868829.143333
912357.06207.67131131131.00000033010.03.3486260.00.0000001.0000006207.670000
customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
568422695.06083.95675675675.01010.04.2560740.00.01.06083.95
568522696.07150.07748748748.01010.04.2925940.00.01.07150.07
568622699.03686.80203203203.01010.05.7723150.00.01.03686.80
568722700.04839.42556262.01010.07.2545160.00.01.04839.42
568822704.017.90777.01010.01.2785710.00.01.017.90
568922705.03.35222.01010.01.6750000.00.01.03.35
569022706.05699.00634634634.01010.04.3209460.00.01.05699.00
569122707.06756.06730730730.00010.04.1759040.00.01.06756.06
569222708.03217.20565959.00010.06.2696610.00.01.03217.20
569322709.03950.72217217217.00010.06.3643780.00.01.03950.72